RGISTools (version 0.9.7)

lsCloudMask: Create cloud masks for Landsat images

Description

lsCloudMask creates a cloud mask derived from the band for quality assurance (BQA) from Landsat-7 or Landsat-8 time series. The function is applied to untarred images, such as those resulting from lsDownSearch or lsDownload. The result is a new image band, called cloud (CLD), that is saved as separate GTiffs.

Usage

lsCloudMask(src, AppRoot, sensitivity = 2800, overwrite = FALSE,
  verbose = FALSE, ...)

Arguments

src

the path to the folder with the untarred images from Landsat-7 or Landsat-8.

AppRoot

the directory where cloud masks are saved.

sensitivity

numeric argument. Defines the sensitivity of the cloud detection method.

overwrite

logical argument. If TRUE, overwrites the existing images with the same name.

verbose

logical argument. If TRUE, the function prints the running steps and warnings.

...

arguments for nested functions.

Value

this function does not return anything. It creates new GTiff files for a new cloud band (CLD) inside the folder of every image.

Details

The valid range for the sensitivity threshold is 0-8000. By defualt, the argument is set to 2800. We recommend 600 and 2800 for Landsat-7 and Landsat-8 respectively.

Examples

# NOT RUN {
# load a spatial polygon object of Navarre
data(ex.navarre)
src <- paste0(tempdir(),"/Path_for_downloading_folder")
print(src)

# search and download images from Landsat-8 between
# 01-01-2018 and 20-01-2018 for the region of Navarre
lsDownload(satellite = "ls8",
           username = "username",
           password = "password",
           startDate = as.Date("01-01-2018", "%d-%m-%Y"),
           endDate = as.Date("20-01-2018", "%d-%m-%Y"),
           pathrow = list(c(200, 31), c(200, 30)),
           untar = TRUE,
           AppRoot = src)
           
# define the path where the GTiff images are located
src.ls8 <- file.path(src,"Landsat8")
src.untar <- file.path(src.ls8,"untar")
# calculate the cloud mask from QC layer
lsCloudMask(src=src.untar,
            overwrite=TRUE,
            AppRoot = src.ls8)
            
# mosaic and crop the imagery
lsMosaic(src = src.untar,
         AppRoot = src.ls8,
         out.name = "Navarre",
         extent = ex.navarre,
         bFilter = c("CLD"),
         gutils = TRUE, # using gdalUtils
         overwrite = TRUE) # overwrite
         
# generate the path where mosaicked images are located
src.navarre <- file.path(src,"Landsat8","Navarre")
# load the B1 layer and calculate the CLD layer
tiles.path <- list.files(src.navarre,
                         full.names = TRUE,
                         recursive = TRUE,
                         pattern = "\\.tif$")
cloud.tiles <- tiles.path[grepl("CLD",tiles.path)]
b1.tiles <- tiles.path[grepl("B1.tif",tiles.path)]
cloud.tiles.ras <- lapply(cloud.tiles,raster)
b1.tiles.ras <- lapply(b1.tiles,raster)

# calculate cloud free b1 layers
b1.cloud.free <- b1.tiles.ras[[1]] * cloud.tiles.ras[[1]]
spplot(b1.cloud.free)
# }